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Assessment of transporter-mediated drug-drug interaction (DDI) is integral to drug development. A risk-based approach leveraging in vitro, in vivo, and in silico information is used to evaluate the DDI liability of drugs and inform the instructions of use. While tremendous advances have been made in recent decades, there are knowledge gaps warranting further research. Herein, we focus on select areas to advance assessment of DDI potential for drugs as substrates, inhibitors, or inducers of certain transporters.

Changes that accompany older age can alter the pharmacokinetics (PK), pharmacodynamics (PD), and likelihood of adverse effects (AEs) of a drug. However, older adults, especially the oldest or those with multiple chronic health conditions, polypharmacy, or frailty, are often under-represented in clinical trials of new drugs. Deficits in the current conduct of clinical evaluation of drugs for older adults and potential steps to fill those knowledge gaps are presented in this communication. The most important step is to increase clinical trial enrollment of older adults who are representative of the target treatment population. Unnecessary eligibility criteria should be eliminated. Physical and financial barriers to participation should be removed. Incentives could be created for inclusion of older adults. Enrollment goals should be established based on intended treatment indications, prevalence of the condition, and feasibility. Relevant clinical pharmacology data need to be obtained early enough to guide dosing and reduce risk for participation of older adults. Relevant PK and PD data as well as patient-centered outcomes should be measured during trials. Trial data should be analyzed for differences in PK, PD, effectiveness, and safety arising from differences in age or from the presence of conditions common in older adults. Postmarket evaluations with real-world evidence and drug labeling updates throughout the product lifecycle reflecting new knowledge are also needed. A comprehensive plan is needed to ensure adequate evaluation of the safety and effectiveness of drugs in older adults.

Evaluating the potential of new drugs and their metabolites to cause drug-drug interactions (DDIs) is critical for understanding drug safety and efficacy. Although multiple analyses of proprietary metabolite testing data have been published, no systematic analyses of metabolite data collected according to current testing criteria have been conducted. To address this knowledge gap, 120 new molecular entities approved between 2013 and 2018 were reviewed. Comprehensive data on metabolite-to-parent area under the curve ratios (AUCM /AUCP ), inhibitory potency of parent and metabolites, and clinical DDIs were collected. Sixty-four percent of the metabolites quantified in vivo had AUCM /AUCP ≥ 0.25 and 75% of these metabolites were tested for cytochrome P450 (CYP) inhibition in vitro, resulting in 15 metabolites with potential DDI risk identification. Although 50% of the metabolites with AUCM /AUCP

A treatment gap exists for pediatric patients with renal impairment. Alterations in renal clearance and metabolism of drugs render standard dosage regimens inappropriate and may lead to drug toxicity, but these studies are not routinely conducted during drug development. The objective of this study was to examine the clinical evidence behind current renal impairment dosage recommendations for pediatric patients in a standard pediatric dosing handbook. The sources of recommendations and comparisons included the pediatric dosing handbook (Lexicomp), the U.S. Food and Drug Administration-approved manufacturer’s labels, and published studies in the literature. One hundred twenty-six drugs in Lexicomp had pediatric renal dosing recommendations. Only 14% (18 of 126) of Lexicomp pediatric renal dosing recommendations referenced a pediatric clinical study, and 15% of manufacturer’s labels (19 of 126) described specific dosing regimens for renally impaired pediatric patients. Forty-two products had published information on pediatric renal dosing, but 19 (45%) were case studies. When pediatric clinical studies were not referenced in Lexicomp, the renal dosing recommendations followed the adult and pediatric dosing recommendations on the manufacturer’s label. Clinical evidence in pediatric patients does not exist for most renal dosing recommendations in a widely used pediatric dosing handbook, and the adult renal dosing recommendations from the manufacturer’s label are currently the primary source of pediatric renal dosing information.

Model-informed drug development (MIDD) refers to the application of a wide range of quantitative models in drug development to facilitate the decision-making process. MIDD was formally recognized in Prescription Drug User Fee Act (PDUFA) VI. There have been many regulatory applications of MIDD to address a variety of drug development and regulatory questions. These applications can be broadly classified into four categories: dose optimization, supportive evidence for efficacy, clinical trial design, and informing policy. Case studies, literature papers, and published regulatory documents are reviewed in this article to highlight some common features of these applications in each category. In addition to the further development and investment in these established domains of application, new technology, and areas, such as more mechanistic models, neural network models, and real-world data/evidence, are gaining attention, and more submissions and experiences are being accumulated to expand the application of model-based analysis to a wider scope.

Our recent studies have shown that chronic kidney disease (CKD) affects the pharmacokinetics (PKs) of cytochrome P450 (CYP)2D6-metabolized drugs, whereas effects were less evident on CYP3A4/5. Therefore, the effect of CKD on the disposition of CYP1A2-metabolized, CYP2C8-metabolized, CYP2C9-metabolized, CYP2C19-metabolized, and organic anion-transporting polypeptide (OATP)-transported drugs was investigated. We identified dedicated CKD studies with 6, 5, 6, 4, and 12 "model" substrates for CYP1A2, CYP2C8, CYP2C9, CYP2C19, and OATP, respectively. Our analyses suggest that clearance of OATP substrates decreases as kidney function declines. Similar trends were seen for CYP2C8; but overlap between some CYP2C8 and OATP substrates highlights that their interplay needs further investigation. In contrast, the effect of CKD on CYP1A2, CYP2C9, and CYP2C19 was variable and modest compared to CYP2C8 and OATP. This improved understanding of elimination-pathway-dependency in CKD is important to inform the need and conduct of PK studies in these patients for nonrenally eliminated drugs.

We evaluated the relative contribution of CYP3A in the overall clearance of commonly used combined oral contraceptives (COCs) based on the results of clinical DDI studies in the literature and new drug applications (NDAs). The results revealed a limited role of CYP3A4 in the metabolism of COC components. Characterization of inhibition or induction spectrum of perpetrators on non‐CYP3A pathways might also be crucial in predicting drug interaction potential of an investigational new drug with COCs.

Recent reviews suggest that chronic kidney disease (CKD) can affect the pharmacokinetics of nonrenally eliminated drugs, but the impact of CKD on individual elimination pathways has not been systematically evaluated. In this study we developed a comprehensive dataset of the effect of CKD on the pharmacokinetics of CYP2D6‐ and CYP3A4/5‐metabolized drugs. Drugs for evaluation were selected based on clinical drug–drug interaction (CYP3A4/5 and CYP2D6) and pharmacogenetic (CYP2D6) studies. Information from dedicated CKD studies was available for 13 and 18 of the CYP2D6 and CYP3A4/5 model drugs, respectively. Analysis of these data suggested that CYP2D6‐mediated clearance is generally decreased in parallel with the severity of CKD. There was no apparent relationship between the severity of CKD and CYP3A4/5‐mediated clearance. The observed elimination‐route dependency in CKD effects between CYP2D6 and CYP3A4/5 may inform the need to conduct clinical CKD studies with nonrenally eliminated drugs for optimal use of drugs in patients with CKD.

The US Food and Drug Administration (FDA) public workshop, entitled “Application of Physiologically-based Pharmacokinetic (PBPK) Modeling to Support Dose Selection focused on the role of PBPK in drug development and regulation. Representatives from industry, academia, and regulatory agencies discussed the issues within plenary and panel discussions. This report summarizes the discussions and provides current perspectives on the application of PBPK in different areas, including its utility, predictive performance, and reporting for regulatory submissions.

Background Rivaroxaban is an oral Factor Xa inhibitor. The primary objective of this communication was to quantitatively predict changes in rivaroxaban exposure when individuals with varying degrees of renal impairment are co-administered with another drug that is both a P-gp and a moderate CYP3A4 inhibitor. Methods A physiologically based pharmacokinetic (PBPK) model was developed to simulate rivaroxaban pharmacokinetics in young (20–45 years) or older (55–65 years) subjects with normal renal function, mild, moderate and severe renal impairment, with or without concomitant use of the combined P-gp and moderate CYP3A4 inhibitor, erythromycin. Results The simulations indicate that combined factors (i.e., renal impairment and the use of erythromycin) have a greater impact on rivaroxaban exposure than expected when the impact of these factors are considered individually. Compared with normal young subjects taking rivaroxaban, concurrent mild, moderate or severe renal impairment plus erythromycin resulted in 1.9-, 2.4- or 2.6-fold increase in exposure, respectively in young subjects; and 2.5-, 2.9- or 3.0-fold increase in exposure in older subjects. Conclusions These simulations suggest that a drug–drug–disease interaction is possible, which may significantly increase rivaroxaban exposure and increase bleeding risk. These simulations render more mechanistic insights as to the possible outcomes and allow one to reach a decision to add cautionary language to the approved product labeling for rivaroxaban. Copyright © 2012 John Wiley & Sons, Ltd.

The issue of drug–drug interactions has generated significant concern within the pharmaceutical industry and amongst regulatory authorities in recent years. This has arisen with respect to early termination of clinical development (e.g. furafylline), refusal of approval (e.g. mibefradil in Sweden), severe prescribing restrictions and withdrawal from the market (e.g. sorivudine, terfenadine, mibefradil, astemizole, cisapride), and threatened litigation. This report summarizes the outcomes of a conference held in Basel in November 2000, under the auspices of the European Federation of Pharmaceutical Sciences (EUFEPS), the US Food and Drug Administration (FDA) and the American Association of Pharmaceutical Sciences (AAPS). The meeting followed on from two previous workshops on drug interactions held in Nuremberg (1997) and Arlington (1999) sponsored by the same groups. Whereas previous conferences had identified the main areas of contention, a specific aim of this meeting was to attempt a consensus on the conduct of in vitro and in vivo studies of metabolic and transport interactions. There were five main conference sessions, in which experienced scientists from academia, industry and regulatory bodies were invited to contribute short presentations formulated, where possible, to address specific questions: Session 1. Mechanistic considerations. Moderators: S. E. Clarke, S. Wrighton; Speakers: A. Boobis, J. B. Houston, S. D. Hall, S. Ekins, P. Maurel, H. Lennernaes. Session 2. In vitro assessment;Moderators: J. B. Houston, K. Thummel; Speakers: B. G. Lake, J. Lipscomb, T. Lave, R. S. Obach, S. Wrighton, S. E. Clarke, P. Langguth, L. Z. Benet, C. Crespi, E. LeCluyse. Session 3: In vitro prediction. Moderators: G. T. Tucker, L. Z. Benet; Speakers: K. Thummel, T. Andersson, B. Clement, H. Suzuki, V. Fischer, M. Dickens, J. Lin, P. Watkins, A. Rostami-Hodjegan. Session 4: In vivo assessment. Moderators: S-M. Huang, U. Fuhr; Speakers: K. S. Reynolds, R. A. Branch, G. Blakey, G. T. Tucker, U. Fuhr, V. Steinijans, P. Milligan, G. Alvan. Session 5: The regulatory view. Moderator: G. Alvan; Speakers: S-M. Huang, Y. Ohno. In addition, the speakers were organized into panels with chairpersons and rapporteurs to develop position statements on the main issues in breakout sessions. These were then presented in open forum at the final session and modified to take account of debate. We have attempted to distil the key features of the discussions with respect to resolved and unresolved issues.

Recent advances in in vitro metabolism methods have led to an improved ability to predict clinically relevant metabolic drug-drug interactions. To address the relationships of in vitro metabolism data and in vivo metabolism outcomes, the Office of Clinical Pharmacology and Biopharmaceutics in the Center for Drug Evaluation and Research, Food and Drug Administration, evaluated a number of recently approved new drug applications. The goal of these evaluations was to determine the contribution of in vitro metabolism data in (1) predicting in vivo drug-drug interactions, (2) determining the need to conduct an in vivo drug-drug interaction study, and (3) incorporating findings into drug product labeling. Ten cases are presented in this article. They fall into two major groups: (1) in vitro data were predictive of in vivo results, and (2) in vitro data were not predictive of in vivo results. Discussion of these cases highlights factors limiting predictability of in vivo metabolic interactions from in vitro metabolism data. The integration of these findings into drug product labeling is also discussed.

Chronic kidney disease, or renal impairment (RI) can increase plasma levels for drugs that are primarily renally cleared and for some drugs whose renal elimination is not a major pathway. We constructed physiologically based pharmacokinetic (PBPK) models for 3 nonrenally eliminated drugs (sildenafil, repaglinide, and telithromycin). These models integrate drug-dependent parameters derived from in vitro, in silico, and in vivo data, and system-dependent parameters that are independent of the test drugs. Plasma pharmacokinetic profiles of test drugs were simulated in subjects with severe RI and normal renal function, respectively. The simulated versus observed areas under the concentration versus time curve changes (AUCR, severe RI/normal) were comparable for sildenafil (2.2 vs 2.0) and telithromycin (1.6 vs 1.9). For repaglinide, the initial, simulated AUCR was lower than that observed (1.2 vs 3.0). The underestimation was corrected once the estimated changes in transporter activity were incorporated into the model. The simulated AUCR values were confirmed using a static, clearance concept model. The PBPK models were further used to evaluate the changes in pharmacokinetic profiles of sildenafil metabolite by RI and of telithromycin by RI and co-administration with ketoconazole. The simulations demonstrate the utility and challenges of the PBPK approach in evaluating the pharmacokinetics of nonrenally cleared drugs in subjects with RI.

Distribution kinetics of gentamicin in whole blood were studied. After spiking human blood to an initial concentration of 20 microgram ml-1, plasma gentamicin concentrations dropped to minima at about 5 min then increased to maxima at about 15 min and remained constant afterwards. A difference of up to 36 per cent between the maximum and minimum was found. The equilibration was faster with lower initial concentrations. These unusual distribution phenomena might be attributed to the Schiff base formation between nonprotonated amino groups of gentamicin and free fatty aldehyde groups on blood cell membrane. The mean equilibrium blood cells/plasma partition ratio was about 0.1. Similar equilibration kinetics were observed with blood of rabbits after being intravenously dosed with gentamicin. Therefore, the time elapsed between the collection and centrifugation of blood samples, especially shortly after dosing, may have a significant effect on the 'measured' plasma gentamicin concentration. Distribution between plasma and blood cells may also occur in a similar manner with other drugs which have primary amino groups. It is recommended that distribution kinetics of drugs and metabolites in blood be included in pharmacokinetic studies.

Etintidine HCl is a potent H2-blocker. The effect of clinical doses of etintidine on the disposition of theophylline was investigated in 10 male volunteers. This was a double-blind, two-way crossover study. Each subject received etintidine (400 mg) or placebo twice a day with meals for 4 days on two occasions (separated by 4 days). On each occasion, the subjects were fasted overnight on Day 3 and were given an oral dose of theophylline elixir (5 mg/kg) 30 min following the administration of the morning dose of etintidine or placebo on Day 4. Blood samples were collected prior to and up to 24 h following the administration of theophylline. Plasma theophylline levels were analysed by HPLC. Theophylline was rapidly absorbed following oral administration of the theophylline elixir to both the placebo and etintidine treatment groups. Comparison of the pharmacokinetic parameters of theophylline between the etintidine and the placebo groups indicates that while etintidine did not significantly (p greater than 0.05) affect the apparent Cmax (11.1 vs 10.0 micrograms ml-1) and Tmax (1.7 vs 1.4 h) values of theophylline, etintidine significantly reduced the oral clearance (0.0200 vs 0.0564 l kg-1 h-1, p = 0.000006) and prolonged the elimination half-life (16.8 vs 6.0 h) of theophylline. The data indicate that etintidine, like cimetidine, extended the elimination of theophylline in humans.

The pharmacokinetics of etintidine (E), a potent H2 blocker, were studied in 12 normal, fasted subjects. The subjects received five ascending doses of E HCl in capsules at 72-h intervals. Blood and urine samples were collected and the plasma and urine levels of E were determined by HPLC. Following oral administration, plasma E levels showed double peaks in half of the subjects. Mean Cmax (0.42, 2.11, 3.82, 4.50, and 7.15 micrograms ml-1), AUC0-infinity (0.96, 4.94, 11.3, 17.5, and 24.5 h micrograms ml-1), and the amount of E excreted unchanged in 72 h (20, 54.8, 170, 320, and 371 mg) were determined. These parameters indicate the amount of E absorbed increased linearly with dose for each individual. Renal clearance was independent of the dose and the mean value (16.6 lh-1) was about twice that of the creatinine clearance (which did not significantly change as a result of E treatment), indicating that E is actively secreted into the renal tubules. As E was eliminated rapidly from the body (t1/2 less than 2 h), no substantial accumulation of E is expected after multiple dose treatment.